Quality control of data

ABSTRACT

A method of monitoring the quality of data comprises sampling a data trace to determine the amplitude of the trace. Attributes that are indicative of the noise content of the data trace are then determined from the sampled amplitudes of the first data trace. The noise attributes of a particular data trace can be compared with pre-set threshold values or with the attributes determined for another data trace, thereby providing a method monitoring the quality of the data. The sampling process is performed in the time domain, and requires only a small amount of computation. The quality control can therefore be carried out on-line, so that the quality of the data can be monitored as it is acquired. The method can be applied to the quality control of seismic data.

[0001] The present invention relates to a method of monitoring thequality of acquired data. In particular, the present invention relatesto a method of monitoring the quality of seismic data that can becarried out while seismic data is being acquired, so as to provideon-line quality control of the acquired data.

[0002] It is highly desirable to provide quality control of dataacquired during seismic exploration in real-time. By “real-time” ismeant that the results of the quality control are produced atsubstantially the same rate that data is acquired; this is also known as“on-line” quality control. Providing on-line quality control during aseismic survey enables any deterioration in quality of the acquiredseismic data that might occur during the survey, for example as a resultof the onset of a fault in a seismic source or a seismic receiver, to bedetected and investigated while the survey is still in progress. In theabsence of on-line quality control such a deterioration in the qualityof the data would only become apparent once the data was analysed afterthe completion of the survey. In order to perform quality controlon-line it is necessary to minimise the amount of computation requiredto perform the quality control, owing to the large amount of data thatis acquired in a typical seismic survey.

[0003] A known method of providing on-line quality control of seismicdata is based on determining the route-mean-square (RMS) amplitude of aseismic data trace. The RMS amplitude of a seismic data trace is acharacteristic of the energy of the trace. Such a prior art on-linequality control method is illustrated schematically in FIG. 1. It can beseen that threshold levels are set for the normalised RMS amplitude of aseismic data trace, and the thresholds are used to classify a trace. Inthe example of FIG. 1, a trace having a normalised RMS amplitude between0.0 and 0.1 is classified as a “dead” trace, a trace having a normalisedRMS amplitude in the range 0.1 to 0.3 is classified as a “weak” trace,and a trace having a RMS amplitude in the range 0.7 to 1.0 is classifiedas a “noisy” trace. Acceptable traces have a RMS amplitude value in therange 0.3 to 0.7.

[0004] The RMS amplitudes of data traces are normalised using, forexample, the expected amplitude of a data trace in a particular surveygeometry having regard to the energy of the seismic source.

[0005] This prior art method of on-line quality control monitors onlythe RMS amplitude of the seismic data traces acquired in a seismicsurvey. The RMS amplitude of a seismic data trace is indicative of theenergy of the seismic data, so that this prior art method monitors onlythe energy of the seismic data traces. Hence, the classification of thetraces into “dead”, “weak”, “good” and “noisy” traces is based solely onthe strength of the signal, and does not provide any information as towhether or not the signal is useful. Moreover, it is not possible forthis prior art method to provide on-line monitoring of furthercharacteristics of the seismic data, because the amount of computationthat this would require could not be carried out at the same rate as theseismic data was acquired.

[0006] The present invention provides a method of monitoring the qualityof data comprising the steps of: sampling a first data trace todetermine the amplitude of the trace at a plurality of sampling times;and determining first and second attributes for the first data tracefrom the sampled amplitudes of the first data trace, the first andsecond attributes being indicative of the noise content of the firstdata trace.

[0007] The method of the present invention enables two or moreattributes that relate to the noise content of the acquired data tracesto be monitored on-line. This provides improved quality control comparedwith the prior art method that monitors just the energy of the datatraces.

[0008] The method of the present invention involves sampling a datatrace to determine the amplitude of the trace at intervals after thestart time of the trace. (In the case of a seismic data trace, forexample, this generally corresponds to the time at which the seismicsource is actuated). Thus, the invention requires only time domainprocessing, and does not require frequency domain processing. Thisreduces the amount of computation required to determine the attributesof the data, and so allows the method of the invention to monitor morethan one attribute of the data.

[0009] In a preferred embodiment, the method comprises the further stepof comparing one of the first and second attributes determined for thefirst data trace with a predetermined threshold value. This providesinformation about the quality of the data trace relative to a pre-setthreshold.

[0010] In an alternative embodiment, the method comprises the furthersteps of: sampling a second data trace to determine the amplitude at aplurality of sampling times; determining the first and second attributesfor the second data trace from the sampled amplitudes of the second datatrace; and comparing at least one of the first and second attributesdetermined for the first data trace with the corresponding one(s) of thefirst and second attributes determined for the second data trace. Thisembodiment provides a measure of the relative quality of the first andsecond data traces. If the first and second data traces are, forexample, seismic data traces that were acquired in the same shot, thiscomparison provides information about the relative quality of traceswithin a shot; alternatively if the first and second data traces are,for example, seismic data traces that were acquired in different shotsthis comparison provides information about the relative quality oftraces from different shots.

[0011] In a preferred embodiment, the or each data trace is a seismicdata trace.

[0012] Preferred features of the present invention are set out in thedependent claims.

[0013] Preferred embodiments of the present invention will now bedescribed in detail by way of illustrative example with reference to theaccompanying figures in which:

[0014]FIG. 1 is a schematic illustration of a prior art method ofon-line quality control of seismic data;

[0015]FIG. 2 is a flow diagram illustrating an embodiment of the presentinvention;

[0016]FIG. 3 illustrates the use of the present invention to monitor theconsistency of seismic data traces with one another;

[0017]FIG. 4 shows the relationship between the amplitude spectraldensity and the frequency;

[0018]FIG. 5 shows the noise spectral density for a typical seismictrace in the presence of machine noise and ambient noise;

[0019]FIG. 6 is a schematic illustration of an overall timing schedulefor the method of the present invention;

[0020]FIG. 7 is a schematic illustration of a detailed timing schedulefor a method of the present invention;

[0021]FIG. 8 is a flow diagram illustrating a real-time quality controlmethod incorporating a method of the present invention; and

[0022]FIG. 9 is a summary of the statistics of attributes generated by amethod of the present invention.

[0023] A method according to one embodiment of the present invention isshown schematically in the flow chart of FIG. 2. This figure illustratesa method of monitoring on-line the quality of a series of seismic datatraces. Initially at step 1 a seismic data trace is obtained, and atstep 2 the seismic trace is sampled. In the sampling process, theamplitude of the trace is measured for predetermined times from thestart of the trace. The interval between successive sampling operationsis preferably constant, so that the interval between any two successivesampling operations defines a sampling frequency F, which is simply theinverse of the time interval between adjacent sampling operations. Thesampling step produces a set of pair of values (t_(i), x_(i)), wherex_(i) is the sampled amplitude of the trace at time t_(i). The set of(t_(i), x_(i)) for a trace are stored.

[0024] For a typical seismic trace having a duration of 5 to 20 secondsa suitable interval between successive sampling operations would be 2 msor 4 ms, corresponding to a sampling frequency of 500 Hz or 250 Hzrespectively.

[0025] From the results of sampling the amplitude of the seismic datatrace, characteristics of the seismic data trace are determined at step3. These are known as “trace keys”. As will be discussed below, thesetrace keys represent features such as the RMS amplitude of the trace, orthe high or low frequency content of the trace.

[0026] At step 4, attributes that are indicative of the noise level inthe seismic trace are determined from the trace keys. As will bediscussed below, it is possible to derive noise attributes that relateto, for example, the spike content of the seismic trace, or the low orhigh frequency component of the seismic data trace.

[0027] Once the trace attributes have been determined they are stored ina suitable database at step 5.

[0028] Steps 1 to 5 are then repeated for a second seismic data trace,to determine and store the trace attributes for a second data trace. Itis now possible to monitor the quality of the acquired seismic data bycomparing the attributes of the second trace with the attributes of thefirst trace at step 6. The first and second traces may relate to thesame shot, in which case a comparison of the attributes of the twotraces provides information about the consistency of traces within asingle shot. Accordingly, the two traces may relate to different shots,in which case the comparison of their attributes provides informationabout the consistency of the data between successive shots. These twopossibilities are illustrated schematically in FIG. 3.

[0029] The results of the comparisons of the attributes of the first andsecond databases may also be stored in a suitable database, at step 7.

[0030] At step 8 the “trace qualifier” is determined. The tracequalifier of a trace is derived from all the attributes determined for atrace, and provides an overall rating of an individual trace.

[0031] At step 9 the “shot rating” is determined. The shot rating isderived from the trace qualifiers of all traces in a shot, and providesan overall rating of an entire shot.

[0032] In addition to comparing the trace noise attributes of the firsttrace with the trace noise attributes of the second seismic data trace,it is possible to compare the trace noise attributes of either of thedata traces with predetermined thresholds. This provides an indicationas to whether the quality of the seismic data meets the desired levels.This enables the data acquired for a particular shot to be given aquality rating that relates to the quality of the data as measuredagainst the pre-set thresholds.

[0033] The method of the invention of providing on-line quality controlof seismic data preferably includes means for checking that the tracekeys derived by sampling the seismic data traces are accuraterepresentations of the actual trace keys of the trace. In the embodimentof FIG. 2 this checking is done by carrying out a full quality controlprocessing of the seismic data at step 10, and the trace keys derivedfrom the process of sampling the seismic data traces are compared withthe results of this full quality control processing of the seismic dataat step 11. The amount of computation required to carry out a fullquality control processing of the seismic data means that it is notpossible to do this in real-time for every trace, so it can be done onlyfor selected shots, in the embodiment of FIG. 2 for every M^(th) shot. Mis typically equal to 50.

[0034] A further feature of the invention is that, because theattributes derived for the seismic data traces and the results of thetrace consistency and shot consistency comparisons are stored in adatabase, it is possible to monitor how the trace attributes, forexample, vary over time. Once data for sufficient traces has beenstored, it is possible to predict the noise attributes of future tracesfrom the stored data at step 12.

[0035] One embodiment of a method for determining the trace keys and thetrace attributes of a seismic data trace will now be described indetail.

[0036] The first step of determining the trace keys for a seismic datatrace is to sample the seismic data trace and obtain measurements of theamplitude of the seismic data trace. The amplitude measured by thei^(th) sampling operation will be denoted as x_(i). The index i runsfrom 1 to N, where N is the total number of times that the trace wassampled.

[0037] In this embodiment, the time interval between each samplingoperation is constant, and the reciprocal of this time interval definesa sampling frequency F.

[0038] Once the seismic data trace has been sampled, the sampledamplitudes are used to define the values of a plurality of functions ofthe sample amplitudes. These functions are known hereinafter as “tracekey values”. The functions can involve, for example, the RMS average ofthe sampled amplitudes, the derivative with respect to time of thesampled amplitudes, or the integral with respect to time of the sampledamplitudes.

[0039] In this embodiment, four trace key values are calculated, usingthe following formulas: $\begin{matrix}{{RMS} = \sqrt{\frac{1}{N}{\sum\limits_{i = 1}^{N}\quad x_{i}^{2}}}} & (1)\end{matrix}$

 MAX={square root}{square root over (max)}(x _(i) ²)  (2)$\begin{matrix}{{RLOF} = {F\sqrt{\frac{1}{N}{\sum\limits_{i = 1}^{N}\quad \left( {\int_{x_{i}}^{\quad}\quad {t}} \right)^{2}}}}} & (3) \\{{RHIF} = {\frac{1}{F}\sqrt{\frac{1}{N}{\sum\limits_{i = 1}^{N}\quad \left( {\frac{\quad}{t}x_{1}} \right)^{2}}}}} & (4)\end{matrix}$

[0040] The first trace key, RMS, is the RMS (route-mean-square) averageof the amplitudes measured in the sampling operations on the seismicdata trace. The trace key RMS is a measure of the RMS amplitude of theseismic data trace.

[0041] The second trace key, MAX, is a measure of the maximum amplitudeof the seismic data trace. It is determined by squaring the sampledamplitudes, and taking the square root of the largest resultant value.

[0042] The third and fourth trace keys RLOF and RHIF are measures of thelow frequency signal components contained in the seismic data trace andthe high frequency signal components contained in the seismic datatrace, respectively. It will be seen that the value RHIF is obtainedfrom the time derivative of the sampled trace, and that the value RLOFis obtained from the integral with respect of time of the sampledamplitudes. The differential with respect to time corresponds to amultiplication by frequency in the frequency domain, whereas integrationwith respect to time corresponds to a division by the frequency in thefrequency domain. Accordingly, the differential with respect to timeused in the calculation of the RHIF value will attenuate the signal atlow frequencies and amplify the signal at high frequencies. Thus, thetrace key RHIF which contains the RMS value of the time derivativeprovides a measure of the high frequency content of the seismic datatrace.

[0043] Conversely, the integral with respect to time, which correspondsto a division by the frequency in the frequency domain, amplifies thesignal at low frequencies and attenuates the signal at high frequencies.Thus, the trace key RLOF which contains the integral of the sampledamplitudes with respect to time provides a measure of the low frequencycontent of the seismic data trace.

[0044]FIG. 4 is a schematic illustration showing how integrating withrespect to time amplifies the low frequency content of the raw signaland attenuates the high frequency content of the raw signal, whereasdifferentiating with respect to time attenuates the low frequencycontent of the raw signal and amplifies the high frequency content ofthe raw signal.

[0045] It will be seen that calculating the trace key RLOF comprises themultiplication by the sampling frequency F, and that calculating thetrace key RHIF comprises division by the sampling frequency F. This isdone in order to provide equal magnitude levels for the values RMS, RLOFand RHIF.

[0046] The trace key values described above are determined from RMSamplitude values that are obtained by processing the seismic data in thetime domain, by sampling the seismic data trace. This is possiblebecause Parseval's theorem states that the RMS value can be determinedeither in the time domain or in the frequency domain, so that it ispossible to determine the RMS value in the more convenient of the timedomain or frequency domain.

[0047]FIG. 4 shows that the RMS value of the time integral of thesampled amplitudes and the RMS value of the time derivative of thesampled values intersect at a frequency f_(x). The frequency range istherefore split into two frequency bands, namely f<f_(x) and f>f_(x).The intersection frequency f_(x) can be scaled using a scaling factorCOR which is related to the sampling frequency F as follows:

COR=F/(CONST.f _(x))  (5)

[0048] In equation (5), CONST is a constant value.

[0049]FIG. 5 is a schematic illustration of the spectral density ofnoise in typical seismic data, plotted as a function of frequency. Itwill be seen that in the mid-frequency range the predominant noise isground roll noise. At low frequencies the noise is predominantly machinenoise, whereas at high frequencies the noise is predominantly machine ortraffic noise, or weather-related noise. It is preferable to scale theintersection frequency f_(x) so that it is approximately equal to thecentre frequency of the frequency range of the ground roll noise. Thisenables useful information to be obtained about both high frequency andlow frequency noise in the trace.

[0050] Once the trace keys have been determined, a plurality ofattributes indicative of the noise of the seismic data trace are thencalculated. These attributes are referred to as “trace noise attributes”hereinafter. In this embodiment of the invention three trace noiseattributes are calculated, as follows:

SPIKE={square root}2 RMS/MAX

LOFRE=RMS/(RLOF/COR)

HIFRE=RMS/(RHIF/COR)

[0051] The noise attribute SPIKE is indicative of the amount of spikenoise in the trace. The noise attribute LOFR is indicative of the amountof low frequency noise in the trace, whereas the noise attribute HIFR isindicative of the amount of high frequency noise in the trace.

[0052] It is possible to determine the type of signal from knowledge ofthe three noise attributes SPIKE, LOFR, and HIFR. In this example, thiscan be done using the following table. TABLE Signal Type SPIKE LOFREHIFRE pure low frequency type 1 0.5 to 1   0 to 0.5 spikes 0 to 0.5 0.5to 1 0.5 to 1 low frequency noise 1   0 to 0.5 0.5 to 1 high frequencynoise 1 0.5 to 1   0 to 0.5 sweep 1 0.5 to 1 0.5 to 1 low frequencywavelet 0 to 0.5   0 to 0.5 0.5 to 1

[0053] It should be noted that the above table represents simply oneexample of the way in which the signal type can be determined from thenoise attributes of a trace, and other classification systems can beused. In other schemes, the threshold values for the noise attributes donot necessarily need to be in the range from 0 to 1.

[0054] Once the noise attributes SPIKE, LOFR, and HIFR have beendetermined for a trace they are stored, for example on magnetic tape ordisk or on other suitable storage media.

[0055] The process of determining the trace keys and the trace noiseattributes is then repeated for a second trace, and the trace noiseattributes of the second trace are also stored. It is then possible tocompare the trace noise attributes of the two traces with one another.This provides a measure of the consistency of the two traces with oneanother. If the two traces relate to the same shot, information isobtained about the consistency of seismic data within the shot.Alternatively, if the two traces are from different shots, a comparisonof their noise attributes provides information about the consistency ofthe acquisition process between shots.

[0056] As noted above, the RMS amplitude of a seismic data trace is ameasure of the energy of the trace. In a preferred embodiment of theinvention, therefore, a comparison is also made between the trace keyRMS of the two data traces. This comparison provides information as towhether the energy characteristic of the signal has changed between thetraces.

[0057] As explained above, the present invention requires a relativelysmall amount of data to characterise the signals by the noise attributesSPIKE, LOFR, and HIFR. The present invention therefore allows the timeevolution of the noise attributes to be monitored, by comparing thebehaviour of the noise attributes for traces acquired at different timesduring the survey. Thereby, even a small degradation of the seismic datatraces can be observed, by monitoring the variation of the noiseattributes over time. If it is seen that the quality of the seismic datais becoming worse, for example as a result of one of the components ofthe acquisition system malfunctioning, it is possible to carry outmaintenance of the acquisition system to ensure that the acquisition ofgood quality data is not interrupted.

[0058] The step of comparing the noise attributes of one trace with thenoise attributes of another trace provides information as to whether thequality of traces in an acquisition is varying from trace to trace. Thiscomparison process, however, does not provide any information as to theabsolute quality level of the traces. The invention therefore preferablyincludes a step of comparing the quality of the traces with pre-setspecifications to determine whether the quality of the acquired seismicdata traces is acceptable. In one embodiment of the invention this isdone by comparing the noise attributes determined for a seismic datatrace with pre-set threshold values. The threshold values represent thenoise attributes that would be obtained if a reference data trace wasprocessed according to the method of the invention. Depending upon thecomparison of the noise attributes obtained for a seismic data tracewith the pre-set threshold values, the trace can be specified as“noisy”, “good”, “weak”, or “dead”.

[0059] The pre-set threshold values can be chosen once the type of thedata trace has been determined from the noise attributes of the trace,for example by using table 1.

[0060] Since the trace keys for a seismic data trace are determined fromthe sampled amplitudes of the trace, errors may occur in the trace keysas a result of the sampling process. For example, unless the trace issampled at exactly the time when it has its maximum amplitude, the tracekey MAX will be lower than the actual maximum amplitude of the trace. Inorder to ensure that the sampling process is leading to reliable valuesfor the trace keys RMS, MAX, RLOF, and RHIF, selected data traces aresubjected to a full quality control processing. The values of the tracekeys obtained by the full quality control processing of a selected traceare compared with the values obtained by the sampled amplitudes, so thatthe reliability of the trace keys determined from the sampled amplitudescan be checked. If the trace keys are found to be unsatisfactory theoperator is alerted to enable corrective action to be taken. Forexample, the sampling frequency can be increased to improve the accuracyof the sampling process.

[0061] The timing sequence of one embodiment of the method of thepresent invention is illustrated in FIGS. 6 and 7. FIG. 6 gives ageneral overview of the timing schedule, and FIG. 7 is a detail of partof FIG. 6.

[0062] In this embodiment the shots have a constant duration T, andadjacent shots are separated by a time ΔT. The duration of each shot isformed of a sweep time T_(s) and a listening time T_(L).

[0063] The data acquired in a shot is converted and processed in aconventional manner, and is stored in a suitable storage means such as amagnetic tape or disc. The data is also used for the quality-controlmethod of the present invention, and the noise attributes for the datatraces of the n^(th) shot are determined and stored. In the embodimentof the timing scheme shown in FIGS. 6 and 7, the noise attributes of then^(th) trace are determined in the time interval ΔT between the end ofthe n^(th) shot and the start of the (n+1)^(th) shot. In the embodimentof FIGS. 6 and 7 the trace noise attributes of the n^(th) shot arestored in the time period δT₁ at the start of the (n+1)^(th), but thesteps of determining and storing the trace noise attributes of then^(th) shot could be carried out simultaneously.

[0064] Once the trace noise attributes of the traces of the n^(th) shothave been determined, one or more noise attributes of one trace of then^(th) shot can then be compared with the corresponding noise attributeor attributes of another trace in the n^(th) shot to determine traceconsistency attributes for the n^(th) shot. A trace consistencyattribute is a measure of the variation in an attribute between onetrace and another and can be determined by, for example, calculating theratio of the value of a noise attributes of one trace to the value ofthat noise attributes of another one trace.

[0065] One or more of the noise attributes for one or more traces of then^(th) shot can also be compared with the stored value of thecorresponding noise attribute(s) for one or more data traces of previousshots, to determine the shot consistency attributes. A shot consistencyattribute is a measure of the variation in an attribute between a tracein one shot and a trace in another shot. The calculated values for thetrace consistency attributes and the shot constituency attributes arestored, and can also be displayed for example on a VDU so that anoperator can monitor the results of the quality control method duringthe survey.

[0066] In the timing chart of FIGS. 6 and 7 the trace consistencyattributes and the shot consistency attributes are determined inparallel during the time period δT₁, and are stored during the timeperiod δT₂. In principle, however, the trace consistency attributes andthe shot consistency attributes could be determined one after the other.

[0067] The step of comparing the trace noise attributes with pre-setthreshold values is not shown in FIGS. 6 and 7, but this step can becarried out at any time once the trace noise attributes have beendetermined. Similarly, if it is desired to perform the step ofclassifying the type of the trace from the trace noise attributes, thiscan be done at any time once the trace noise attributes have beendetermined.

[0068] It will be seen from FIGS. 6 and 7 that the time required toperform the quality control processing of the present invention issignificantly less than the duration of a shot. That is, the presentinvention provides an on-line quality control method in which thequality of a shot can be determined and displayed to an observer shortlyafter the completion of the shot.

[0069] In the embodiment of FIGS. 6 and 7 full quality controlprocessing is carried out on the data traces of selected shots, tocalibrate the quality control method of the invention. In thisembodiment the time required to carry out the full quality controlprocessing has been shown as approximately equal to, although slightlyless than, the overall duration of fifty shots. The full quality controlprocessing is therefore carried out on the data traces of every fiftiethshot in this embodiment. It should be noted, however, that the inventionis not limited to carrying out full quality control processing on everyfiftieth shot.

[0070]FIG. 8 shows a flow chart of the present invention. At step 20seismic data traces are obtained in a shot, and at step 21 the noiseattributes of the seismic data traces of this shot are determined, forexample by the method described above, and stored. At step 22 the noiseattributes of the data traces of the n^(th) shot are compared withpre-set noise specifications. If the results of the determination atstep 22 is that the traces of the n^(th) shot are classified as “noisy”traces, at step 23 it is determined whether the traces of the n^(th)shot nevertheless satisfy the specifications set down for the acquiredseismic data. If there is a yes determination at step 23 the next shotis fired.

[0071] If there is a “no” determination at step 23, the operator isalerted and the cause of the excessive noise is investigated at step 24.

[0072] If there is a “yes” determination at step 22, the noiseattributes of the seismic data traces of the n^(th) shot are comparedamongst themselves at step 25 to determine the consistency of the tracesof the n^(th) shot. The noise attributes of the seismic data traces ofthe n^(th) shot are also compared with the stored values of noiseattributes determined for to earlier shots at step 26, to determine theshot consistency. At step 27 the trace consistency attributes and theshot consistency attributes are compared with pre-set thresholds todetermine whether the trace consistency and shot consistency attributesare acceptable. If there is a “yes” determination at step 27, the nextshot is fired at step 28.

[0073] If there is a “no” determination at step 27, it is thendetermined at step 23 whether the trace consistency and shot consistencyattributes nevertheless meet the specifications set down for the seismicdata. If there is a “yes” determination at step 23, the next shot isfired at step 28.

[0074] If there is a “no” determination at step 23, the operator isalerted, and at step 24 the cause of the lack of consistency of theseismic data is investigated.

[0075] In FIG. 8, steps 25 and 26 (determination of the traceconsistency attribute and the shot consistency attribute) are carriedout in parallel. As noted above, however, these steps could be carriedout one after the other.

[0076] It is preferable to have the real-time quality control processingof one shot completed before the next shot is fired. In a practical dataacquisition system, however, the system will generally arm the next shotbefore the quality control process on the previous shot has beencompleted. This “one-shot delay” in the completion of the real-timequality control processing does present the risk that one shot could bewasted, through being fired before the operator is made aware of aproblem with the quality of the acquired seismic data of the previousshot. However, the loss of a single shot is generally acceptable inseismic surveying.

[0077] Since the noise attributes determined for each seismic data traceare stored, it is possible to produce statistics illustrating thequality of the seismic data. As an example, FIG. 9 is a schematicillustration of a histogram of the values of the noise attribute SPIKEfor all seismic data traces in one shot. Traces having a value of thenoise attribute SPIKE lower than a first threshold value TH₁ areclassified as “bad traces”, and traces having a value for the noiseattribute SPIKE that exceeds a second threshold value TH₂ are classifiedas “good” traces. The bar-chart shows the relative number of traces thatare classified as “bad” or “good” traces. An operator can monitor forexample, the relative number of “bad” traces, and take action if thisexceeds a pre-set threshold such as 5%. The operator can also monitorthe relative number of “good” traces and take action if this falls belowa pre-set threshold such as 80%.

[0078] Similar bar-charts to the one shown in FIG. 9 can be compiled forthe other noise attributes LOFRE and HIFRE.

[0079] The bar-charts may be continually updated as further shots arerecorded, so that an operator can see at once if there is an increase inthe number of “bad” traces or a decrease in the number of “good” traces.

[0080] The threshold values TH₁ and TH₂ may be pre-set on the basis ofthe type of the seismic data signal as deduced from the noise attributesaccording to table 1.

[0081] In FIG. 9 a shot is classified as “bad” or as “good” on the basisof solely one of the noise attributes. It is also possible to classifytraces as “good” or “bad” on the basis of a consideration of all threeof the noise attributes SPIKE, LOFRE, and HIFRE. For example a tracemight be required to meet respective pre-set thresholds for all threenoise attributes SPIKE, LOFRE, and HIFRE in order to be classified as a“good” trace.

[0082] Although the preferred embodiments of the invention have beendescribed with reference to processing seismic data traces, theinvention is not limited to use with seismic data traces.

1. A method of monitoring the quality of data comprising the steps of:sampling a first acquired data trace to determine the amplitude of thetrace at a plurality of sampling times; and determining first and secondattributes for the acquired first data trace from the sampled amplitudesof the first acquired data trace, the first and second attributes beingindicative of the noise content of the first acquired data trace.
 2. Amethod as claimed in claimed in claim 1 and comprising the further stepof comparing one of the first and second attributes determined for thefirst data trace with a predetermined threshold value.
 3. A method asclaimed in claim 1 or 2 and comprising the further steps of: sampling asecond data trace to determine the amplitude at a plurality of samplingtimes; determining the first and second attributes for the second datatrace from the sampled amplitudes of the second data trace; andcomparing at least one of the first and second attributes determined forthe first data trace with the corresponding one(s) of the first andsecond attributes determined for the second data trace.
 4. A method asclaimed in claim 1, 2 or 3 and further comprising the step of predictingat least one of the first and second attributes of a third data tracefrom the attributes determined for the first data trace and/or theattributes determined for the second data trace.
 5. A method as claimedin any preceding claim and further comprising the step of identifyingthe type of the data represented by the first and/or second data tracefrom the values of the attributes determined for the first and/or seconddata trace.
 6. A method as claimed in any preceding claim and furthercomprising the step of determining a third attribute indicative of thenoise content of the first or second data trace from the sampledamplitudes of the first or second data trace.
 7. A method as claimed inany preceding claim wherein one of the attributes is indicative of thespike content of a data trace.
 8. A method as claimed in any of claims 1to 6 wherein one of the attributes is indicative of the low frequencycontent of a data trace.
 9. A method as claimed in any of claims 1 to 6wherein one of the attributes is indicative of the high frequencycontent of a data trace.
 10. A method as claimed in any preceding claimwherein the step of determining the attributes of a data trace comprisesdetermining the values of a plurality of functions of the sampledamplitudes of the data trace, and calculating the attributes of the datatrace from the values of the functions.
 11. A method as claimed in claim10 wherein one of the functions is the RMS average of the sampledamplitudes.
 12. A method as claimed in claim 10 wherein one of thefunctions is a function of the derivative with respect to time of thesampled amplitudes.
 13. A method as claimed in claim 10 wherein one ofthe functions is a function of the integral with respect to time of thesampled amplitudes.
 14. A method as claimed in any of claims 10 to 13wherein the step of determining the values of the plurality of functionsof the sampled amplitudes comprises determining the four values RMS,MAX, RLOF, and RHIF, where${RMS} = \sqrt{\frac{1}{N}{\sum\limits_{i = 1}^{N}\quad x_{i}^{2}}}$

MAX={square root}{square root over (max)}(x _(i) ²) $\begin{matrix}{{RLOF} = {F\sqrt{\frac{1}{N}{\sum\limits_{i = 1}^{N}\quad \left( {\int{x_{i}{t}}} \right)^{2}}}}} \\{{RHIF} = {\frac{1}{F}\sqrt{\frac{1}{N}{\sum\limits_{i = 1}^{N}\quad \left( {\frac{\quad}{t}x_{1}} \right)^{2}}}}}\end{matrix}$

where F is the sampling frequency, x_(i) is the amplitude measured inthe i^(th) sampling operation and 1≦i≦N.
 15. A method as claimed inclaim 14 wherein the step of determining the attributes indicative ofthe noise content of the trace comprises determining the attributes:SPIKE={square root}2RMS/MAX;LOFRE=RMS/(RLOF/COR);HIFRE=RMS/(RHIF COR);where COR=F/(CONST.f_(x)), and f_(x) is the frequency at whichLOFRE=HIFRE.
 16. A method as claimed in any preceding claim wherein theor each data trace is a seismic data trace.
 17. A method as claimed inclaim 16 when dependent from claim 3 or from any claim dependent fromclaim 3, wherein the first and second data traces were acquired in thesame shot.
 18. A method as claimed in claim 16 when dependent from claim3 or from any claim dependent from claim 3, wherein the first and seconddata traces were acquired in different shots.